Alzheimer's disease is classified as a degenerative dementia while vascular dementia is known to be associated with atherothrombosis and classical vascular risk factors. However, over the last decade, there is increasing evidence of the role of haemostatic factors and inflammatory mechanisms in the pathogenesis of Alzheimer's disease. Serum markers of hypercoagulability and markers of inflammation could lead to thrombosis, accelerated atherogenesis and resulting dementia of both Alzheimer's and vascular dementia. In this case control study, we studied these serum markers of coagulation and inflammation in patients suffering from dementia.
A novel coronavirus (SARS-CoV-2) is an unusual viral pneumonia in patients, first found in late December 2019, latter it declared a pandemic by World Health Organizations because of its fatal effects on public health. In this present, cases of COVID-19 pandemic are exponentially increasing day by day in the whole world. Here, we are detecting the COVID-19 cases, i.e., confirmed, death, and cured cases in India only. We are performing this analysis based on the cases occurring in different states of India in chronological dates. Our dataset contains multiple classes so we are performing multi-class classification. On this dataset, first, we performed data cleansing and feature selection, then performed forecasting of all classes using random forest, linear model, support vector machine, decision tree, and neural network, where random forest model outperformed the others, therefore, the random forest is used for prediction and analysis of all the results. The K-fold cross-validation is performed to measure the consistency of the model.
Universally accessible and publically archived nature of Bug Tracking System (BTS) of Open Source Software enables developers to follow the work of each other and contribute in bug fixing. The interaction of developers through comments on BTS of project leads to form a social network. The developers and their relationships change over the time resulting in evolution of Developers' social network (DSN). Prior studies (Hong et.al) have compared the evolution of DSN with evolution of general social networks like facebook, twitter etc., showing their resemblance and some differences with them. However these studies don't provide any insight how the evolution of DSN correlate with the effectiveness of bug fixing process over the time. Such insight is helpful as managers can reorganize the teams and issue the guidelines to the developers, accordingly, forcing the communication structure which results in to more effective bug fixing process. In this paper, we first study the evolution of DSN of Eclipse a java based IDE, partially replicating and enhancing the study done by Hong et. al. Then we show how the global social network properties of the DSN e.g. Average Path Length, Clustering Coefficient, modularity etc. has an impact on attributes characterizing effectiveness of bug fixing process like average fix time of the bugs, percentage of bugs fixed etc. We found good correlation between global social network properties and attributes characterizing the bug fixing process.
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